DCE-MRI Perfusion Analysis with L1-Norm Spatial Regularization

0499809 - ÚPT 2019 US eng A - Abstract
Bartoš, Michal - Šorel, Michal - Mangová, M. - Rajmic, P. - Standara, M. - Jiřík, Radovan
DCE-MRI Perfusion Analysis with L1-Norm Spatial Regularization.
Joint Annual Meeting ISMRM-ESMRMB 2018. Book of Absdtracts.. Concord: ISMRM, 2018.
[Joint Annual Meeting ISMRM-ESMRMB 2018. 16.06.2018-18.06.2018, Paris]
R&D Projects: GA ČR(CZ) GA16-13830S
Institutional support: RVO:68081731 ; RVO:67985556
Keywords : MRI * perfusion analysis * pharmacokinetic modeling * spatial regularization * total variation
OECD category: Medical laboratory technology (including laboratory samples analysis; Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8) (UTIA-B)

DCE-MRI perfusion analysis suffers from low reliability, especially when 2. generation pharmacokinetic models are used to estimate perfusion parameter maps (voxel-by-voxel estimation) in low SNR conditions. These models provide estimates of plasma flow and capillary permeability in addition to the commonly used parameters Ktrans , k(ap). This contribution presents a method for estimation of perfusion maps using the tissue homogeneity model with incorporated spatial regularization in the form of total variation. The algorithm is based on the proximal minimization methods well established in image reconstruction problems. The use of state-of-the-art minimization and image regularization techniques stabilizes the estimates of perfusion parameter maps and keeps the computational demands low.
Permanent Link: http://hdl.handle.net/11104/0291995